September 2026

The rapid expansion of software systems and the growing number of reported vulnerabilities have emphasized the importance of accurately identifying vulnerable code segments. Traditional methods for vu

Skeleton-based video anomaly detection has gained significant attention in security and forensics applications due to its privacy-preserving properties that abstract human motion without capturing ide

Electric Vehicles (EVs) now function as both energy consumers and producers within the energy internet-enabled smart grid, enabling bidirectional energy exchange with the grid. To facilitate secure Ve

Text-to-image (T2I) models can be exploited to produce unsafe images. Existing safety measures, e.g., content moderation or model alignment, can be weakened by adversaries who attempt to restore unsaf

Optical Coherence Tomography (OCT) has emerged as a powerful technique for capturing subcutaneous internal fingerprints (IF) and internal sweat pores (ISP), offering enhanced security over surface bio

As Retrieval-Augmented Generation (RAG) brings Large Language Models (LLMs) into contact with proprietary and user-specific knowledge bases in sensitive domains, protecting the privacy of both queries

In Incorrect-Plaintext Attacks (IPA), a malicious Data Owner (DO) compromises system security by encrypting incorrect plaintext, while a malicious Data User (DU) undermines system fairness by falsely

Encrypted traffic analysis (ETA) plays a critical role in detecting malicious activities. Although machine learning-based ETA has shown significant promise, existing methods heavily depend on large-sc

The human hand serves as a vital biometric modality, with the palm, fingers, and knuckles commonly employed for identity recognition across a range of applications. Despite the abundance of sensitive

The rapid advancement of generative adversarial networks and diffusion-based models has enabled the creation of highly realistic synthetic images, raising urgent concerns regarding the authenticity of